Warning: This analysis contains the results of a predictive model that was not prepared or reviewed by an epidemiologist. The assumptions and methods presented should be considered carefully before arriving at any conclusions.

Based on data up to: 2020-05-16

World map (interactive)

Includes only countries with at least 1000 reported cases or at least 20 reported deaths.

Tip: Select columns to show on map to from the dropdown menus. The map is zoomable and draggable.

Tables

Projected need for ICU beds

Countries sorted by current ICU demand, split into Growing and Recovering countries by current infection rate.

  • Details of estimation and prediction calculations are in Appendix, as well as Plots of model predictions.
  • Column definitions:- Estimated ICU need per 100k population: number of ICU beds estimated to be needed per 100k population by COVID-19 patents. - Estimated daily infection rate: daily percentage rate of new infections relative to active infections during last 5 days.
    • Projected ICU need per 100k in 14 days: self explanatory.
    • Projected ICU need per 100k in 30 days: self explanatory.
    • ICU capacity per 100k: number of ICU beds per 100k population.
    • Estimated ICU Spare capacity per 100k: estimated ICU capacity per 100k population based on assumed normal occupancy rate of 70% and number of ICU beds (only for countries with ICU beds data).

Tip: The red (need for ICU) and the blue (ICU spare capacity) bars are on the same 0-10 scale, for easy visual comparison of columns.

Growing countries (infection rate above 5%)

Estimated
current
ICU need
per 100k
population
Estimated
daily infection
rate
Projected
ICU need
per 100k
In 14 days
Projected
ICU need
per 100k
In 30 days
ICU
capacity
per 100k
Estimated ICU
Spare capacity
per 100k
Country/Region
Qatar 32.16 8.5% ± 0.9% 49.7 ± 10.1 83.3 ± 36.4 - -
Kuwait 11.43 11.0% ± 1.2% 27.1 ± 7.3 noisy data - -
Bahrain 11.17 8.4% ± 1.5% 17.4 ± 6.6 noisy data - -
Singapore 11.08 5.2% ± 0.6% 11.4 ± 1.8 11.7 ± 4.0 11.4 3.4
Belarus 8.28 6.0% ± 0.2% 9.4 ± 0.4 11.1 ± 1.1 - -
Peru 7.97 8.0% ± 0.5% 11.4 ± 1.1 17.5 ± 3.7 - -
Chile 6.59 10.1% ± 1.3% 13.5 ± 4.6 noisy data - -
Maldives 6.33 5.3% ± 1.7% 6.6 ± 2.2 noisy data - -
UAE 5.64 6.7% ± 0.2% 7.0 ± 0.4 9.1 ± 1.2 - -
Russia 5.57 6.3% ± 0.5% 6.5 ± 0.6 7.9 ± 1.6 8.3 2.5
Sweden 5.30 5.6% ± 0.3% 5.5 ± 0.5 5.6 ± 1.1 5.8 1.7
Saudi Arabia 4.35 7.6% ± 0.5% 6.1 ± 0.6 9.1 ± 2.0 22.8 6.8
Armenia 3.80 8.4% ± 0.7% 5.8 ± 1.0 9.7 ± 3.8 - -
Brazil 3.53 9.7% ± 1.1% 6.5 ± 1.7 noisy data - -
Ecuador 3.18 5.7% ± 1.7% noisy data noisy data - -
Moldova 3.10 7.6% ± 0.7% 4.3 ± 0.9 6.2 ± 2.9 - -
Oman 2.92 11.5% ± 1.6% 7.6 ± 3.1 noisy data 14.6 4.4
Dominican Republic 2.50 5.3% ± 0.9% 2.6 ± 0.6 noisy data - -
Gabon 2.35 12.7% ± 2.9% noisy data noisy data - -
Iran 1.75 5.8% ± 0.2% 1.9 ± 0.2 2.2 ± 0.4 4.6 1.4
Mexico 1.10 8.1% ± 0.5% 1.6 ± 0.2 2.6 ± 0.6 1.2 0.4
Bolivia 1.09 8.7% ± 0.8% 1.8 ± 0.3 3.1 ± 1.2 - -
Ukraine 0.95 5.1% ± 0.2% 1.0 ± 0.1 1.0 ± 0.1 - -
Poland 0.87 5.6% ± 0.8% 0.9 ± 0.3 noisy data 6.9 2.1
Colombia 0.83 8.3% ± 0.4% 1.3 ± 0.1 2.1 ± 0.4 - -
Honduras 0.80 6.1% ± 3.1% noisy data noisy data - -
South Africa 0.74 9.3% ± 0.3% 1.3 ± 0.1 2.6 ± 0.5 - -
Azerbaijan 0.70 7.9% ± 1.0% 1.0 ± 0.3 noisy data - -
Tajikistan 0.64 17.2% ± 5.1% noisy data noisy data - -
El Salvador 0.64 8.0% ± 2.0% 1.0 ± 0.4 noisy data - -
Ghana 0.58 5.6% ± 2.8% noisy data noisy data - -
Afghanistan 0.54 9.1% ± 1.0% 0.9 ± 0.2 noisy data - -
Guinea 0.53 7.6% ± 2.7% noisy data noisy data - -
Pakistan 0.50 noisy data noisy data noisy data 1.5 0.4
Senegal 0.44 7.7% ± 0.6% 0.6 ± 0.1 1.0 ± 0.3 - -
Argentina 0.41 8.5% ± 0.4% 0.6 ± 0.1 1.1 ± 0.3 - -
Bangladesh 0.41 8.4% ± 0.8% 0.6 ± 0.1 1.1 ± 0.4 0.7 0.2
Algeria 0.35 5.9% ± 0.1% 0.4 ± 0.0 0.5 ± 0.0 - -
Guatemala 0.34 13.2% ± 2.4% noisy data noisy data - -
Egypt 0.30 6.3% ± 0.4% 0.4 ± 0.0 0.4 ± 0.1 - -
Cameroon 0.26 5.9% ± 2.4% noisy data noisy data - -
Somalia 0.25 6.9% ± 2.5% noisy data noisy data - -
Sudan 0.21 noisy data noisy data noisy data - -
Sierra Leone 0.20 noisy data noisy data noisy data - -
Philippines 0.20 5.2% ± 0.3% 0.2 ± 0.0 0.2 ± 0.0 2.2 0.7
India 0.20 7.6% ± 0.4% 0.3 ± 0.0 0.4 ± 0.1 5.2 1.6
Cote d'Ivoire 0.17 7.3% ± 1.9% noisy data noisy data - -
Iraq 0.16 6.7% ± 1.0% 0.2 ± 0.1 noisy data - -
Indonesia 0.14 7.2% ± 0.6% 0.2 ± 0.0 0.3 ± 0.1 2.7 0.8
Uzbekistan 0.14 5.1% ± 0.9% 0.1 ± 0.0 noisy data - -
Chad 0.11 9.8% ± 2.5% 0.2 ± 0.1 noisy data - -
Mali 0.10 6.1% ± 0.5% 0.1 ± 0.0 0.1 ± 0.0 - -
Nigeria 0.09 5.5% ± 0.9% 0.1 ± 0.0 0.1 ± 0.0 - -
Kenya 0.04 6.3% ± 1.5% 0.0 ± 0.0 noisy data - -

Recovering countries (infection rate below 5%)

Estimated
current
ICU need
per 100k
population
Estimated
daily infection
rate
Projected
ICU need
per 100k
In 14 days
Projected
ICU need
per 100k
In 30 days
ICU
capacity
per 100k
Estimated ICU
Spare capacity
per 100k
Country/Region
US 7.46 4.7% ± 0.2% 6.9 ± 0.4 6.3 ± 0.7 34.7 10.4
United Kingdom 6.15 4.1% ± 0.0% 5.2 ± 0.1 4.2 ± 0.1 6.6 2.0
Ireland 6.12 2.8% ± 0.5% 4.5 ± 1.2 noisy data 6.5 1.9
Belgium 5.06 2.6% ± 0.1% 3.5 ± 0.2 2.3 ± 0.3 15.9 4.8
Panama 4.03 4.5% ± 0.1% 3.7 ± 0.1 3.4 ± 0.3 - -
Canada 3.63 4.1% ± 0.0% 3.2 ± 0.0 2.7 ± 0.1 13.5 4.0
Spain 3.50 1.9% ± 0.0% 2.3 ± 0.1 1.3 ± 0.1 9.7 2.9
Luxembourg 3.15 1.9% ± 0.0% 2.1 ± 0.1 1.2 ± 0.2 24.8 7.4
Portugal 3.12 3.2% ± 0.1% 2.4 ± 0.1 1.8 ± 0.2 4.2 1.3
Italy 2.86 2.7% ± 0.1% 2.1 ± 0.2 1.4 ± 0.2 12.5 3.8
Turkey 2.52 3.5% ± 0.0% 2.1 ± 0.0 1.6 ± 0.1 47.1 14.1
Netherlands 2.46 2.3% ± 0.1% 1.7 ± 0.1 1.1 ± 0.1 6.4 1.9
France 2.14 1.4% ± 0.2% 1.3 ± 0.2 0.7 ± 0.3 11.6 3.5
Denmark 2.12 2.5% ± 0.1% 1.5 ± 0.1 1.0 ± 0.1 6.7 2.0
Djibouti 2.10 4.6% ± 0.5% 2.0 ± 0.4 1.9 ± 0.8 - -
Switzerland 1.72 1.3% ± 0.0% 1.1 ± 0.0 0.6 ± 0.0 11.0 3.3
Serbia 1.57 2.0% ± 0.1% 1.1 ± 0.0 0.7 ± 0.1 - -
Finland 1.56 3.1% ± 0.4% 1.2 ± 0.2 0.9 ± 0.4 6.1 1.8
Germany 1.54 2.2% ± 0.1% 1.1 ± 0.1 0.7 ± 0.1 29.2 8.8
Iceland 1.49 0.2% ± 0.0% 0.8 ± 0.0 0.4 ± 0.0 9.1 2.7
Romania 1.43 3.7% ± 0.2% 1.2 ± 0.1 1.0 ± 0.1 - -
Israel 1.33 0.8% ± 0.0% 0.8 ± 0.0 0.4 ± 0.0 - -
North Macedonia 1.09 3.9% ± 0.4% 0.9 ± 0.2 0.8 ± 0.3 - -
Bosnia 1.04 3.3% ± 0.3% 0.8 ± 0.1 0.6 ± 0.2 - -
Austria 0.91 3.5% ± 0.1% 0.7 ± 0.1 0.6 ± 0.2 21.8 6.5
Norway 0.89 1.9% ± 0.0% 0.6 ± 0.0 0.4 ± 0.0 8.0 2.4
Estonia 0.85 2.2% ± 0.1% 0.6 ± 0.0 0.4 ± 0.1 14.6 4.4
Kazakhstan 0.72 4.5% ± 0.5% 0.7 ± 0.1 0.6 ± 0.2 21.3 6.4
Czechia 0.65 3.5% ± 0.2% 0.5 ± 0.1 0.4 ± 0.1 11.6 3.5
Bulgaria 0.58 4.2% ± 0.3% 0.5 ± 0.0 0.5 ± 0.1 - -
Hungary 0.52 3.4% ± 0.3% 0.4 ± 0.1 0.3 ± 0.1 13.8 4.1
Lithuania 0.46 3.5% ± 0.2% 0.4 ± 0.1 0.3 ± 0.1 15.5 4.6
Albania 0.42 4.7% ± 0.7% 0.4 ± 0.1 noisy data - -
Croatia 0.39 1.5% ± 0.2% 0.2 ± 0.0 0.1 ± 0.0 - -
Morocco 0.35 3.2% ± 0.5% 0.3 ± 0.0 0.2 ± 0.1 - -
Slovenia 0.33 0.6% ± 0.0% 0.2 ± 0.0 0.1 ± 0.0 6.4 1.9
Kyrgyzstan 0.33 4.4% ± 1.2% 0.3 ± 0.1 noisy data - -
Slovakia 0.24 2.4% ± 0.2% 0.2 ± 0.0 0.1 ± 0.0 9.2 2.8
Cuba 0.23 2.6% ± 0.4% 0.2 ± 0.0 0.1 ± 0.0 - -
Greece 0.20 3.9% ± 0.4% 0.2 ± 0.1 noisy data 6.0 1.8
Malaysia 0.19 2.1% ± 0.2% 0.1 ± 0.0 0.1 ± 0.0 3.4 1.0
Japan 0.15 1.8% ± 0.2% 0.1 ± 0.0 0.1 ± 0.0 7.3 2.2
Lebanon 0.15 3.8% ± 0.3% 0.1 ± 0.0 0.1 ± 0.0 - -
New Zealand 0.13 0.3% ± 0.0% 0.1 ± 0.0 0.0 ± 0.0 - -
Australia 0.12 2.1% ± 0.1% 0.1 ± 0.0 0.1 ± 0.0 9.1 2.7
Tunisia 0.06 0.6% ± 0.1% 0.0 ± 0.0 0.0 ± 0.0 - -
Niger 0.05 4.5% ± 0.8% 0.0 ± 0.0 noisy data - -
South Korea 0.05 4.3% ± 0.1% 0.0 ± 0.0 0.0 ± 0.0 10.6 3.2
Burkina Faso 0.04 2.3% ± 0.4% 0.0 ± 0.0 0.0 ± 0.0 - -
Thailand 0.02 0.6% ± 0.1% 0.0 ± 0.0 0.0 ± 0.0 10.4 3.1
Tanzania 0.01 0.0% ± 0.0% 0.0 ± 0.0 0.0 ± 0.0 - -
China 0.00 1.1% ± 0.0% 0.0 ± 0.0 0.0 ± 0.0 3.6 1.1

Appendix

Interactive plot of Model predictions

Tip: Choose a country from the drop-down menu to see the calculations used in the tables above and the dynamics of the model.

Projected Affected Population percentage

Countries sorted by number of new cases in last 5 days. The projected affected population percentage is directly related to the calculation of estimated ICU need.

  • Details of estimation and prediction calculations are in Appendix, as well as Plots of model predictions.
  • Column definitions:
    • Estimated new cases in last 5 days: self explanatory.
    • Estimated total affected population percentage: estimated percentage of total population already affected (infected, recovered, or dead).
    • Estimated daily infection rate: daily percentage rate of new infections relative to active infections during last 5 days.
    • Projected total affected percentage in 14 days: of population.
    • Projected total affected percentage in 30 days: of population.
    • Lagged fatality rate: reported total deaths divided by total cases 8 days ago.
Estimated
new cases
in last 5 days
Estimated
total
affected
population
percentage
Estimated
daily infection
rate
Projected
total
affected
percentage
In 14 days
Projected
total
affected
percentage
In 30 days
Lagged
fatality
rate
Country/Region
US 1,151,541 4.3% 4.7% ± 0.2% 5.2% ± 0.1% 6.3% ± 0.3% 6.9%
Brazil 946,568 1.7% 9.7% ± 1.1% 3.7% ± 0.6% 8.2% ± 3.2% 10.7%
United Kingdom 386,532 8.1% 4.1% ± 0.0% 9.5% ± 0.0% 10.9% ± 0.1% 16.2%
Mexico 240,488 0.9% 8.1% ± 0.5% 1.6% ± 0.1% 2.9% ± 0.4% 16.0%
India 132,838 0.0% 7.6% ± 0.4% 0.1% ± 0.0% 0.1% ± 0.0% 4.8%
Peru 111,768 1.6% 8.0% ± 0.5% 2.8% ± 0.2% 5.1% ± 0.7% 4.1%
Italy 100,467 7.6% 2.7% ± 0.1% 8.0% ± 0.1% 8.3% ± 0.2% 14.6%
Russia 95,131 0.4% 6.3% ± 0.5% 0.6% ± 0.0% 0.9% ± 0.1% 1.4%
Iran 83,814 1.3% 5.8% ± 0.2% 1.6% ± 0.0% 2.0% ± 0.1% 6.6%
Canada 70,742 2.5% 4.1% ± 0.0% 2.9% ± 0.0% 3.4% ± 0.0% 8.6%
Sweden 60,747 6.1% 5.6% ± 0.3% 7.7% ± 0.3% 9.8% ± 0.9% 14.5%
Spain 56,036 8.5% 1.9% ± 0.0% 8.8% ± 0.1% 8.9% ± 0.1% 12.4%
France 45,206 6.0% 1.4% ± 0.2% 6.1% ± 0.2% 6.2% ± 0.3% 15.6%
Ecuador 42,169 2.5% 5.7% ± 1.7% 3.2% ± 0.8% noisy data 9.3%
Belgium 37,035 11.5% 2.6% ± 0.1% 12.2% ± 0.2% 12.7% ± 0.3% 17.3%
Turkey 34,821 0.7% 3.5% ± 0.0% 0.8% ± 0.0% 0.9% ± 0.0% 3.0%
Indonesia 31,864 0.1% 7.2% ± 0.6% 0.1% ± 0.0% 0.2% ± 0.0% 8.3%
Pakistan 29,471 0.1% noisy data 0.1% ± 0.1% noisy data 3.2%
Colombia 25,873 0.2% 8.3% ± 0.4% 0.4% ± 0.0% 0.8% ± 0.1% 5.6%
Chile 25,646 0.5% 10.1% ± 1.3% 1.2% ± 0.2% noisy data 1.6%

Methodology & Assumptions

  • I'm not an epidemiologist. This is an attempt to understand what's happening, and what the future looks like if current trends remain unchanged.
  • Everything is approximated and depends heavily on underlying assumptions.
  • Countries with less than 10 total deaths or less than 1 Million population are excluded.
  • Projection is done using a simple SIR model with (see examples) combined with the approach in Total Outstanding Cases:
    • Growth rate calculated over the 5 past days. This is pessimistic - because it includes the testing rate growth rate as well, and is slow to react to both improvements in test coverage and "flattening" due to social isolation.
    • Confidence bounds are calculated by from the weighted STD of the growth rate over the last 5 days. Model predictions are calculated for growth rates within 1 STD of the weighted mean. The maximum and minimum values for each day are used as confidence bands.
    • For projections (into future) very noisy projections (with broad confidence bounds) are not shown in the tables.
    • Recovery probability being 1/20 (for 20 days to recover) where the rate estimated from Total Outstanding Cases is too high (on down-slopes).
  • ICU need is calculated as being 4.4% of active reported cases where:
    • Active cases are taken from the SIR model. The ICU need is calculated from reported cases rather than from total estimated active cases. This is because the ICU ratio (4.4%) is based on symptomatic reported cases.
    • ICU capacities are from Wikipedia (OECD countries mostly) and CCB capacities in Asia.
    • ICU spare capacity is based on 70% normal occupancy rate (66% in US, 75% OECD)
  • Total case estimation calculated from deaths by:
    • Assuming that unbiased fatality rate is 0.72% (current meta estimate in).
    • The average fatality lag is assumed to be 8 days on average for a case to go from being confirmed positive (after incubation + testing lag) to death. This is the same figure used by "Estimating The Infected Population From Deaths".
    • Testing bias: the actual lagged fatality rate is than divided by the 0.72% figure to estimate the testing bias in a country. The estimated testing bias then multiplies the reported case numbers to estimate the true case numbers (=case numbers if testing coverage was as comprehensive as in the heavily tested countries).
    • The testing bias calculation is a high source of uncertainty in all these estimations and projections. Better source of testing bias (or just true case numbers), should make everything more accurate.